A multi-criteria approach to bid selection in public procurement

Business forms such as the goods and services sales to state-owned enterprises, due to its secure billing, are extremely attractive for private businesses and as such are susceptible to possible misuse. When there is the possibility of corruption, regardless of whether it takes place, not only the protection of the procurers' rights must be discussed, but also the protection of all parties involved in public procurement processes. The aim of this paper is to give a possible multi-criteria methodology for selecting the optimal of the submitted bids within the public procurement tender. According to the Public Procurement Law in Serbia, the procurement contracting authority is required to define the criteria for the winning tender with valued weights. The contribution of this paper lies within the new methodology which enables procurator to use transparent, unique and, by Public Procurement Law, correct way of choosing the best one from bids submitted within public procurement tender

COMPARATIVE STUDY: FEATURE SELECTION METHODS IN THE BLENDED LEARNING ENVIRONMENT

Research presented in this paper deals with the unknown behavior pattern of students in the blended learning environment. In order to improve prediction accuracy it was necessary to determine the methodology for students` activities assessments. The Training set was created by combining distributed sources – Moodle database and traditional learning process. The methodology emphasizes data mining preprocessing phase: transformation and features selection. Information gain, Symmetrical Uncert Feature Eval, RelieF, Correlation based Feature Selection, Wrapper Subset Evaluation, Classifier Subset Evaluator features selection methods were implemented to find the most relevant subset. Statistical dependence was determined by calculating mutual information measure. Naïve Bayes, Aggregating One-Dependence Estimators, Decision tree and Support Vector Machines classifiers have been trained for subsets with different cardinality. Models were evaluated with comparative analysis of statistical parameters and time required to build them. We have concluded that the RelieF, Wrapper Subset Evaluation and mutual information present the most convenient features selection methods for blended learning environment. The major contribution of the presented research is selecting the optimal low-cardinal subset of students’ activities and a significant prediction accuracy improvement in blended learning environment

Opportunities to revitalise rural tourism through the operation of agrarian cooperatives

Agrarian cooperatives are still in a period of transition. Practice shows that it is necessary to reconsider the business activities performed in the sector. Under the 2015 Cooperatives Act, rural tourism was recognised as a business activity, but the legal move has had no practical implications. In order to identify opportunities for the revitalisation of rural tourism, a study has been carried out based on interviews with the general managers of agrarian cooperatives. Their views have been analysed to gauge their awareness of the effects of rural tourism on rural areas arising from the operation of cooperatives, and the potential of human resources to implement the consequent organisational changes. In addition, the potential of agrarian cooperatives has been explored in the context of external surroundings. The results of the research have shown that the general managers view positively the revitalisation of rural tourism as part of the operation of the cooperatives, and that they are aware of the favourable impacts of tourism on rural areas, but that incompetence of the staff in the cooperatives has been a main obstacle to such a development